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Franziska Hufsky

Researcher at University of Jena

Publications -  33
Citations -  1100

Franziska Hufsky is an academic researcher from University of Jena. The author has contributed to research in topics: Medicine & String (computer science). The author has an hindex of 16, co-authored 30 publications receiving 859 citations. Previous affiliations of Franziska Hufsky include Max Planck Society & Schiller International University.

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Computational mass spectrometry for small molecules

TL;DR: This review covering the computational aspects of identifying small molecules, from the identification of a compound searching a reference spectral library, to the structural elucidation of unknowns, describes the basic principles and pitfalls of searching mass spectral reference libraries.
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Significance estimation for large scale metabolomics annotations by spectral matching

TL;DR: The authors develop strategies to estimate false discovery rates (FDR) by empirical Bayes and target-decoy based methods which enable a user to define the scoring criteria for spectral matching.
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Identifying the unknowns by aligning fragmentation trees

TL;DR: This work presents a tool for searching a database for compounds with fragmentation pattern similar to an unknown sample compound, and applies this tool to metabolites from Icelandic poppy.
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Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research.

Franziska Hufsky, +54 more
TL;DR: Bioinformatics workflows and tools for the routine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets and development of therapeutic strategies are reviewed.
Journal ArticleDOI

Computational mass spectrometry for small-molecule fragmentation

TL;DR: In this article, the identification of small molecules from mass spectrometry (MS) data remains a major challenge in the interpretation of MS data, and computational aspects of identifying small molecules range from searching a reference spectral library to the structural elucidation of an unknown.